Technologies of computed tomography (CT) have been broadly used for medical examinations. CT images have been used as bases for disease diagnoses for thirty years. Improvement of CT image quality and reduction of image artifacts (artifacts) are conventional, important issues in studies of CT image reconstruction algorithms and clinics.
Typically, the CT image reconstruction algorithms include a filtered back projection algorithm, an image iterative reconstructive algorithm, and an algebraic image reconstruction algorithm. The filtered back projection algorithm is a main stream of CT image reconstructions, and has been widely used in current CT products. In the filtered back projection algorithm, the filtered back projection is performed to projection data acquired by actual scans to acquire image data.
However, in the filtered back projection algorithm, it is assumed that the projection data for image reconstruction is not affected by noise, but the noise always actually exists in association with the projection data. Since the noise is remarkable particularly in low radiation dose scans, it is difficult to acquire high-definition CT images. However, the clinical application range of CT has spread with development of clinical medical examinations, and CT has reached an extremely higher level than before. Under the background of such a new situation, high image quality is newly desired in consideration of the safety at the time of CT usage in the industry. Therefore, it is difficult for the filtered back projection algorithm to meet the new demand, and the filtered back projection algorithm is used for medium or low level clinical applications in many cases.
The iterative reconstructive algorithm is attracting attention in high-level clinical applications with respect to the above new demand. In the image iterative reconstructive algorithm, image artifacts due to electronic noise and other physical factors are processed properly. Thus, image information can be secured, and radiation dose can be reduced during examinations. However, it was not widely used in actual CT products due to huge calculation amount and high calculation cost. With rapid development of computer technology, the iterative reconstructive algorithm can be applied to the actual products. CT image quality is improved, and image artifacts are reduced, and at the same time, radiation dose necessary for projection can be reduced. With development of medicine and health promotion, the influence of X-ray radiation on human bodies during CT diagnoses is considered more important. Thus, there has been a trend toward low dose CT in the development of CT. Therefore, the iterative reconstructive algorithm has attracted more attention, and is an important subject of research. The iterative reconstructive algorithm mainly includes an iterative projection and back projection process looped multiple times.
In the conventional filtered back projection algorithm, the main process is a back projection process, and when the back projection method such as the conventional pixel-driven type (Pixel-Driven) is used, the model error is large. Therefore, new back projection methods are being studied to reduce artifacts and improve image quality.
On the other hand, in the iterative reconstructive algorithm that has attracted attention, the conventional projection and back projection method based on the ray-driven type (Ray-Driven) and pixel-driven type (Pixel-Driven), the model error is large, and when it is applied to the projection and back projection process in the iterative reconstructive algorithm, it is difficult for the algorithm to converge accurately.
Based on the above situation, many new projection and back projection methods have been studied and proposed, and are used in the conventional filtered back projection algorithm, particularly in the iterative reconstruction algorithm that has attracted attention. The most typical methods include the distance-driven type (Distance-Driven) and separable footprint (Separable Footprint) method. In the distance-driven type, two midline intersections of a pixel block are projection points, and higher model accuracy can be acquired than in the ray-driven type and pixel-driven type.
However, in the distance-driven projection and back projection method, the following technical problem is present. The model error is still large in some angular ranges of the projection/back projection to still affect the image quality after the reconstruction remarkably.